Kalman Filter Matlab File

% Update K = P*H' / (H*P*H' + R); x = x + K*(meas(k) - H*x); P = (eye(2) - K*H)*P;

% Kalman loop for k = 1:length(meas) % Predict x = F x; P = F P*F' + Q; kalman filter matlab

Estimate position and velocity from noisy measurements. % Update K = P*H' / (H*P*H' +

% Plot plot(true_pos, 'g-', meas, 'ro', est_pos, 'b--') legend('True', 'Noisy', 'Kalman estimate') P = (eye(2) - K*H)*P